Early detection of high water saturation spots for landslide prediction using thermal image analysis / (Record no. 7773)

MARC details
000 -LEADER
fixed length control field 03735ntm a2200373 i 4500
001 - CONTROL NUMBER
control field vtls000105298
003 - CONTROL NUMBER IDENTIFIER
control field KUKTEM
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251117113402.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180925t20182018my a f a m 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number THE0005166(Local)
039 #9 - LEVEL OF BIBLIOGRAPHIC CONTROL AND CODING DETAIL [OBSOLETE]
Level of rules in bibliographic description 201905141429
Level of effort used to assign nonsubject heading access points hanafiah
Level of effort used to assign subject headings 201905141428
Level of effort used to assign classification hanafiah
-- 201809251538
-- fateeha
040 ## - CATALOGING SOURCE
Original cataloging agency UMP
Language of cataloging eng
Transcribing agency UMP
Description conventions rda
090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN)
Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) FKEE .A94 2018 r Thesis
100 0# - MAIN ENTRY--PERSONAL NAME
Personal name Aufa Huda Muhammad Zin,
Relator term author.
245 10 - TITLE STATEMENT
Title Early detection of high water saturation spots for landslide prediction using thermal image analysis /
Statement of responsibility, etc. Aufa Huda Muhammad Zin
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Kuantan, Pahang :
Name of producer, publisher, distributor, manufacturer UMP,
Date of production, publication, distribution, manufacture, or copyright notice 2018
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice © 2018
300 ## - PHYSICAL DESCRIPTION
Extent xiv, 107 pages :
Other physical details illustrations (some color), color maps ;
Dimensions 30 cm. +
Accompanying material 1 CD-ROM
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
336 ## - CONTENT TYPE
Content type term text
Source rdacontent
337 ## - MEDIA TYPE
Media type term unmediated
Source rdamedia
337 ## - MEDIA TYPE
Media type term computer
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term volume
Source rdacarrier
338 ## - CARRIER TYPE
Carrier type term computer disc
Source rdacarrier
347 ## - DIGITAL FILE CHARACTERISTICS
File type text file
Encoding format PDF
Source rda
500 ## - GENERAL NOTE
General note Faculty of Electrical and Electronics Engineering
502 ## - DISSERTATION NOTE
Dissertation note Thesis (Master of Science) -- Universiti Malaysia Pahang – 2018
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references
520 3# - SUMMARY, ETC.
Summary, etc. Landslide hazard is often discussed in electronic media and newspapers. Due to this problem, the government needs to bear millions of Malaysian ringgit to repair the infrastructures and utilities that had been ruined and to compensate the victims involved. Early warning system is one of the effective ways to reduce damage caused by landslides. Based on the literature found, there are many conventional methods to predict landslide that had been used previously such as remote sensing, wireless sensor network and many more. Basically, landslides happen due the many factors such as slope gradient factor, geological weathering and human-related activities such as deforestation. The main factor for landslide is water saturation, caused by heavy rain. Our naked eyes cannot see the water saturation in the soil. Hence, to solve this issue, this study investigates a new method to detect water saturation spots which is integrated with a thermal image camera to provide early detection of landslide. Thermal camera is selected because it provides accurate predictions on where landslides could occur. Thermal imaging is a technique that converts the invisible radiation into visible image for analysis and feature extraction. The images are processed using image processing software. Performance of image processing software is based on how accurate Region of Interest (ROI) detection is to eliminate unwanted pixels from an image. There are three segmentation algorithm used in this study which are HSV, K-Means and Feature Matching. The result reveals that HSV color space technique provides the best segmentation with average misclassification error equals to 0.00165 for abnormal images, 0.0061 for normal images and 0.0014 for combination of abnormal and normal images. Furthermore, the prediction method should make decision and classify the images into correct groups. Therefore, after the ROI has been detected, feature extraction and classification must be performed. Statistical based features namely minimum, maximum, mean and standard deviation were extracted from each image channels. The results show that the classifications using linear thresholding had sorted the image into correct group successfully.
610 20 - SUBJECT ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Faculty of Electrical and Electronics Engineering
General subdivision Dissertations
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Universities and colleges
General subdivision Disertations
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Theses
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
  Not lost Library of Congress Classification   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   FKEE .A94 2018 r Thesis 0000124998 04/09/2019 1 04/09/2019 Thesis
  Not lost Library of Congress Classification   Not for loan UMPLIB PEKAN UMPLIB PEKAN 04/09/2019   CD 11587 | FKEE .A94 2018 r Thesis 0000124999 04/09/2019 1 04/09/2019 Thesis

Perpustakaan Universiti Malaysia Pahang Al-Sultan Abdullah
26600 Pekan, Pahang Darul Makmur
Phone: +609 431 5063 (Gambang) / +609 431 5035 (Pekan)
Email: umplibrary@umpsa.edu.my

Connect With Us